To tackle the problem of severe air pollution, China has implemented active clean air policies in recent years. As a consequence, the emissions of major air pollutants have decreased and the air quality has substantially improved. Here, we quantified China's anthropogenic emission trends from 2010 to 2017 and identified the major driving forces of these trends by using a combination of bottom-up emission inventory and index decomposition analysis (IDA) approaches. The relative change rates of China's anthropogenic emissions during 2010–2017 are estimated as follows: −62 % for SO₂, −17 % for NO_x, +11 % for nonmethane volatile organic compounds (NMVOCs), +1 % for NH₃, −27 % for CO, −38 % for PM₁₀, −35 % for PM_2.5, −27 % for BC, −35 % for OC, and +16 % for CO₂. The IDA results suggest that emission control measures are the main drivers of this reduction, in which the pollution controls on power plants and industries are the most effective mitigation measures. The emission reduction rates markedly accelerated after the year 2013, confirming the effectiveness of China's Clean Air Action that was implemented since 2013. We estimated that during 2013–2017, China's anthropogenic emissions decreased by 59 % for SO₂, 21 % for NO_x, 23 % for CO, 36 % for PM₁₀, 33 % for PM_2.5, 28 % for BC, and 32 % for OC. NMVOC emissions increased and NH₃ emissions remained stable during 2010–2017, representing the absence of effective mitigation measures for NMVOCs and NH₃ in current policies. The relative contributions of different sectors to emissions have significantly changed after several years' implementation of clean air policies, indicating that it is paramount to introduce new policies to enable further emission reductions in the future.

From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM _2.5 ) concentrations occurred nationwide. Here we estimate the drivers of the improved PM _2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population–weighted annual mean PM _2.5 concentrations decreased from 61.8 (95%CI: 53.3–70.0) to 42.0 µg/m ³ (95% CI: 35.7–48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM _2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM _2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9–7.1), 4.4- (95% CI: 3.8–4.9), 2.8- (95% CI: 2.5–3.0), and 2.2- (95% CI: 2.0–2.5) µg/m ³ declines in the national PM _2.5 concentration in 2017, respectively, and further reduced PM _2.5 -attributable excess deaths by 0.37 million (95% CI: 0.35–0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China’s recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO₂, 52.1 Tg NO_x, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH₃, 31.7 Tg PM₁₀, 22.7 Tg PM_2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO₂. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO₂, +19.2 % for NO_x, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH₃, −3.4 % for PM₁₀, −1.6 % for PM_2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO₂. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

The development of reliable anthropogenic emission inventories is essential for both understanding the sources of air pollution and designing effective air-pollution-control measures in China. However, it is challenging to quantify emissions in China accurately, given the variety of contributing sources, the complexity of the technology mix and the lack of reliable measurements. Over the last two decades, tremendous efforts have been made to improve the accuracy of emission inventories, and significant improvements have been realized. More reliable statistics and survey-based data have been used to reduce the uncertainties in activity rates and technology distributions. Local emission factors and source profiles covering various sources have been measured and reported. Based on these local databases, improved emission inventory models have been developed for power plants, large industrial plants and the residential, transportation and agricultural sectors. In this paper, we review the progress that has been made in developing inventories of anthropogenic emissions in China. We first highlight the major updates that have been made to emission inventory models and the underlying data by source category. We then summarize the sector-based estimates of emissions of different species contained in current inventories. The progress that has been made in the development of model-ready emissions is also presented. Finally, we suggest future directions for further improving the accuracy of emission inventories in China.

Net anthropogenic emissions of carbon dioxide (CO₂) must approach zero by mid-century (2050) in order to stabilize the global mean temperature at the level targeted by international efforts^1,2,3,4,5. Yet continued expansion of fossil-fuel-burning energy infrastructure implies already ‘committed’ future CO₂ emissions^{6,7,8,9,10,11,12,13}. Here we use detailed datasets of existing fossil-fuel energy infrastructure in 2018 to estimate regional and sectoral patterns of committed CO₂ emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of the associated infrastructure. We estimate that, if operated as historically, existing infrastructure will cumulatively emit about 658 gigatonnes of CO₂ (with a range of 226 to 1,479 gigatonnes CO₂, depending on the lifetimes and utilization rates assumed). More than half of these emissions are predicted to come from the electricity sector; infrastructure in China, the USA and the 28 member states of the European Union represents approximately 41 per cent, 9 per cent and 7 per cent of the total, respectively. If built, proposed power plants (planned, permitted or under construction) would emit roughly an extra 188 (range 37–427) gigatonnes CO₂. Committed emissions from existing and proposed energy infrastructure (about 846 gigatonnes CO₂) thus represent more than the entire carbon budget that remains if mean warming is to be limited to 1.5 degrees Celsius (°C) with a probability of 66 to 50 per cent (420–580 gigatonnes CO₂)⁵, and perhaps two-thirds of the remaining carbon budget if mean warming is to be limited to less than 2 °C (1,170–1,500 gigatonnes CO₂)⁵. The remaining carbon budget estimates are varied and nuanced^14,15, and depend on the climate target and the availability of large-scale negative emissions¹⁶. Nevertheless, our estimates suggest that little or no new CO₂-emitting infrastructure can be commissioned, and that existing infrastructure may need to be retired early (or be retrofitted with carbon capture and storage technology) in order to meet the Paris Agreement climate goals¹⁷. Given the asset value per tonne of committed emissions, we suggest that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternatives are available and affordable^4,18.

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in East China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show the haze during the COVID lockdown were driven by enhancements of secondary pollution. In particular, large decreases in NO_x emissions from transportation increased ozone and nighttime NO₃ radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.